CN113672489B - Resource performance level determination method and equipment for super computer - Google Patents

Resource performance level determination method and equipment for super computer Download PDF

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CN113672489B
CN113672489B CN202111237139.4A CN202111237139A CN113672489B CN 113672489 B CN113672489 B CN 113672489B CN 202111237139 A CN202111237139 A CN 202111237139A CN 113672489 B CN113672489 B CN 113672489B
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state value
memory
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supercomputer
cpu
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CN113672489A (en
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聂鹏飞
郑刚
刘腾萧
韩振鑫
康波
孟祥飞
冯景华
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National Supercomputer Center In Tianjin
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
    • G06F11/3466—Performance evaluation by tracing or monitoring
    • G06F11/3476—Data logging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available

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Abstract

The application provides a resource performance level determination method and device of a super computer, computer equipment and a storage medium, relates to the technical field of super computing, and is used for improving the utilization rate of resources of the super computer. The method mainly comprises the following steps: acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer; adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value; and determining the resource performance level of the target super computer according to the system state value and the application state value.

Description

Resource performance level determination method and equipment for super computer
Technical Field
The present application relates to the field of supercomputer technologies, and in particular, to a supercomputer evaluation method and apparatus, a computer device, and a storage medium.
Background
The supercomputer is a computer which is formed by combining a plurality of computing nodes and can perform large-scale computation or data processing in parallel, is also called as a parallel computer, is the computer with the strongest function, the fastest operation and the largest storage capacity, is mainly used for the national high-tech field and the advanced technical research, and is an important embodiment of the national science and technology development level and the comprehensive national force.
At present, more and more super computers are provided with more and more architecture and technical routes, super computing centers in various places, such as bamboo shoots in spring after raining, are in endless, and in the face of such many super computers, users face difficulty in selection, and it is unclear which is better to select.
Disclosure of Invention
The embodiment of the application provides a resource performance level determination method and device for a supercomputer, computer equipment and a storage medium, which are used for improving the utilization rate of supercomputer resources.
The embodiment of the invention provides a resource performance level determination method of a super computer, which comprises the following steps:
acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer;
adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
and determining the resource performance level of the target super computer according to the system state value and the application state value.
The embodiment of the invention provides a resource performance level determining device of a super computer, which comprises:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target super computer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target super computer;
the computing module is used for adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
and the determining module is used for determining the resource performance level of the target super computer according to the system state value and the application state value.
A computer device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, said processor implementing the resource performance level determination method of the above-mentioned supercomputer when executing said computer program.
A computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out the method of resource performance level determination of a supercomputer as described above.
The invention provides a resource performance grade determination method, a device, computer equipment and a storage medium of a supercomputer.A Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer are firstly obtained; then adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value; and finally, determining the resource performance level of the target supercomputer according to the system state value and the application state value. Therefore, the resource performance owned by the super computer can be calculated through the method, the resource performance level corresponding to the super computer can be determined, and the resource utilization rate of the super computer is improved according to the resource new energy level of the super computer.
Drawings
FIG. 1 is a flow chart of a resource performance level determination method for a supercomputer according to the present application;
fig. 2 is a schematic diagram illustrating a memory flow required by an acquisition program according to the present application;
fig. 3 is a schematic structural diagram of a resource performance level determination apparatus of a supercomputer according to the present application.
Detailed Description
In order to better understand the technical solutions described above, the technical solutions of the embodiments of the present application are described in detail below with reference to the drawings and the specific embodiments, and it should be understood that the specific features of the embodiments and the embodiments of the present application are detailed descriptions of the technical solutions of the embodiments of the present application, and are not limitations of the technical solutions of the present application, and the technical features of the embodiments and the embodiments of the present application may be combined with each other without conflict.
Referring to FIG. 1, a method for determining the performance level of a resource of a supercomputer according to the present invention is shown. The method specifically comprises the steps of S10-S30:
step S10, obtaining a CPU state value, a memory state value, a network state value, and an input/output I/O state value of the target supercomputer, and an operating time state value, a CPU utilization rate, and a memory utilization rate required for the target application to operate under the target supercomputer.
Wherein, the target super computer is a computer needing to determine the performance level of the resource. For example, the target supercomputer may be a Tianhe supercomputer Tianhe 1A (TH 1A), a Tianhe model III prototype (TH 3E), a self-built HPC cluster (HPC) of the national supercomputing Tianjin center, and the like, and the embodiment is not particularly limited.
In this embodiment, the CPU state value, the memory state value, the network state value, and the input/output I/O state value are respectively used to represent the CPU performance, the memory performance, the network performance, and the I/O performance of the target supercomputer. Certainly, fine-grained state values of the target supercomputer, such as power consumption test, high-temperature test, pressure test, noise test and the like, can also be obtained, and then calculation is performed according to the state values of all dimensions of the target supercomputer to obtain the system state value of the target supercomputer.
The running time state value is used for evaluating the time occupied by the target application running in the target super computer, the CPU utilization rate is used for evaluating the CPU resource occupied by the target application running in the target super computer, and the memory utilization rate is used for evaluating the memory resource occupied by the target application running in the target super computer.
In an embodiment of the present invention, the step S10 of obtaining the CPU state value, the memory state value, the network state value, and the I/O state value of the target supercomputer includes:
step S101, acquiring first intermediate parameters and second intermediate parameters corresponding to different evaluation types of the target supercomputer.
The evaluation type comprises a CPU, a memory, a network and an I/O. The first intermediate parameter is an intermediate parameter with higher numerical value and better performance, and for example, the first intermediate parameter may specifically be a CPU floating point operation speed, a memory bandwidth, a network bandwidth, a CPU utilization rate, a memory utilization rate, and the like; the second intermediate parameter is an intermediate parameter with a smaller numerical value and better performance, for example, the second intermediate parameter may specifically be running time, network delay, and the like, and the embodiment of the present invention is not specifically limited.
Step S102, calculating the state value of the first intermediate parameter by the following formula:
Figure DEST_PATH_IMAGE002
；
step S103, calculating the state value of the second intermediate parameter by the following formula:
Figure DEST_PATH_IMAGE004
；
and step S104, calculating the sum of the state value of the first intermediate parameter and the state value of the second intermediate parameter belonging to the same evaluation type to obtain a CPU state value, a memory state value, a network state value and an I/O state value.
Wherein the content of the first and second substances,
Figure 8039DEST_PATH_IMAGE005
for the target supercomputer at
Figure DEST_PATH_IMAGE006
The result of the evaluation of the aspect,
Figure DEST_PATH_IMAGE007
in order for the target super-computer to be,
Figure 100002_DEST_PATH_IMAGE008
a first intermediate parameter or a second intermediate parameter respectively corresponding to the evaluation type CPU, the memory, the network and the I/O,
Figure DEST_PATH_IMAGE009
to represent
Figure 793461DEST_PATH_IMAGE008
Higher coefficients, which means that the intermediate parameters are more important, generally coefficients in terms of cpu are most important, followed by network, memory and I/O,
Figure 100002_DEST_PATH_IMAGE010
，
Figure DEST_PATH_IMAGE011
is a fixed value set in advance.
Figure DEST_PATH_IMAGE012
To a target supercomputer
Figure 952758DEST_PATH_IMAGE007
In that
Figure 368696DEST_PATH_IMAGE008
Evaluation results of aspects;
Figure DEST_PATH_IMAGE013
for presetting supercomputers
Figure DEST_PATH_IMAGE014
In that
Figure 744052DEST_PATH_IMAGE008
Aspect evaluation result, presetting supercomputer
Figure 490422DEST_PATH_IMAGE014
And the basic supercomputer is used for measuring the evaluation result of the target supercomputer. In the present embodiment, it is preferred that,benckmarkcomparisons need to be made at equal core numbers.
It should be noted that, in the present embodiment, each performance intermediate parameter of the target supercomputer may be obtained by the system evaluation tool. For example, the embodiment is not specifically limited to this, and the method includes obtaining a memory bandwidth test result through a tool Stream, obtaining a memory pressure test result through a tool memtest, obtaining a metadata operation test result through a tool Mdtest, obtaining a file system test result through a tool IOR, obtaining an IO performance test result through a tool IOzone, obtaining a network performance test result through a tool Osu, obtaining a CPU performance test result through a tool linepack, and the like.
In another embodiment provided by the present invention, the step S10 obtains the runtime state value, the CPU utilization, and the memory utilization required by the target application to run under the target supercomputer, and includes:
and S101, acquiring a third intermediate parameter and a fourth intermediate parameter respectively corresponding to different evaluation types of the target application under the target super computer.
The evaluation type comprises an operation time state value, a CPU utilization rate and a memory utilization rate; the third intermediate parameter is an intermediate parameter with higher numerical value and better performance, and for example, the third intermediate parameter may specifically be a CPU floating point operation speed, a memory bandwidth, a network bandwidth, a CPU utilization rate, a memory utilization rate, and the like; the fourth intermediate parameter is an intermediate parameter with a smaller numerical value and better performance, for example, the fourth intermediate parameter may specifically be running time, network delay, and the like, and the embodiment of the present invention is not specifically limited.
Step S102, calculating the state value of the third intermediate parameter by the following formula:
Figure DEST_PATH_IMAGE016
；
step S103, calculating the state value of the fourth intermediate parameter by the following formula:
Figure 956038DEST_PATH_IMAGE018
；
step S104, calculating the sum of the state value of the third intermediate parameter and the state value of the fourth intermediate parameter belonging to the same evaluation type to obtain an operating time state value, a CPU utilization rate and a memory utilization rate;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE019
running on the target supercomputer for the target application
Figure DEST_PATH_IMAGE020
The result of the evaluation of the aspect,
Figure DEST_PATH_IMAGE021
for the purpose of the said target application(s),
Figure DEST_PATH_IMAGE022
in order for the target super-computer to be,
Figure 729828DEST_PATH_IMAGE020
running time status value, CPU utilization, and memory utilization score for evaluation typeRespectively corresponding third intermediate parameter or fourth intermediate parameter,
Figure DEST_PATH_IMAGE023
to represent
Figure 999004DEST_PATH_IMAGE020
Higher coefficient, indicating that the intermediate parameter is more important,
Figure 100002_DEST_PATH_IMAGE024
，
Figure 142541DEST_PATH_IMAGE011
the value is a fixed value set in advance, and is usually set to 10.
Figure DEST_PATH_IMAGE025
For the target application
Figure DEST_PATH_IMAGE027
At the target supercomputer
Figure 639162DEST_PATH_IMAGE007
On the upper part
Figure 616476DEST_PATH_IMAGE020
Evaluation results of aspects;
Figure DEST_PATH_IMAGE028
for the target application
Figure 389260DEST_PATH_IMAGE021
On a preset super computer
Figure 507127DEST_PATH_IMAGE014
On the upper part
Figure 947335DEST_PATH_IMAGE020
And (4) evaluating results of aspects. Preset super computer
Figure 626710DEST_PATH_IMAGE014
And the basic supercomputer is used for measuring the evaluation result of the target supercomputer. In the present embodiment, it is preferred that,benckmarkcomparisons need to be made at equal core numbers.
Step S20, add the CPU state value, the memory state value, the network state value, and the I/O state value to obtain a system state value, and add the operating time state value, the CPU utilization rate, and the memory utilization rate to obtain an application state value.
In particular, the method is characterized by the formula
Figure DEST_PATH_IMAGE029
Calculating a CPU state value, a memory state value, a network state value and an I/O state value, and then adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value
Figure DEST_PATH_IMAGE030
By the above formula
Figure 526270DEST_PATH_IMAGE019
Calculating the running time state value, the CPU utilization rate and the memory utilization rate, and then adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value
Figure DEST_PATH_IMAGE031
。
And step S30, determining the resource performance level of the target super computer according to the system state value and the application state value.
In particular, by the formula
Figure DEST_PATH_IMAGE032
A resource performance level of the target supercomputer is determined. The resource performance level may be a specific state value, or after obtaining a specific state value, the resource performance level may be determined according to the state value. More specifically, the present embodiment may divide the supercomputer into N according to actual requirementsThe resource performance levels, such as the first level, the second level, and the third level, may be represented by the first level as the optimal resource performance of the supercomputer, the second level as the good resource performance of the supercomputer, and the third level as the poor resource performance level of the supercomputer, which is not specifically limited in this embodiment.
The invention provides a resource performance grade determination method of a supercomputer, which comprises the steps of firstly obtaining a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and obtaining an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer; then adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value; and finally, determining the resource performance level of the target supercomputer according to the system state value and the application state value. Therefore, the resource performance owned by the super computer can be calculated through the method, the resource performance level corresponding to the super computer can be determined, and the resource utilization rate of the super computer is improved according to the resource new energy level of the super computer.
In one embodiment provided by the present invention, the method may further include:
step S201
Figure DEST_PATH_IMAGE033
Programs of different calculation sizes
Figure DEST_PATH_IMAGE034
Are respectively at
Figure DEST_PATH_IMAGE035
Different supercomputers
Figure DEST_PATH_IMAGE036
Provided with
Figure DEST_PATH_IMAGE037
A plurality of different computing resources
Figure 100002_DEST_PATH_IMAGE038
And running to obtain the running time state value, the CPU utilization rate and the memory utilization rate under the corresponding relation among the program, the supercomputer and the computing resources.
And the memory of the node corresponding to the computing resource is larger than the memory required for running the corresponding program.
For example, the user-provided will
Figure 198560DEST_PATH_IMAGE033
Programs of different calculation sizes
Figure 267842DEST_PATH_IMAGE034
Are respectively at
Figure 101806DEST_PATH_IMAGE035
Different supercomputers
Figure 131073DEST_PATH_IMAGE036
Provided with
Figure 341474DEST_PATH_IMAGE037
A plurality of different computing resources
Figure 897220DEST_PATH_IMAGE038
The operation is carried out. Wherein computing resources
Figure DEST_PATH_IMAGE039
Taking a computing node providing high-performance computing power as a unit, the number of distributed nodes is required to meet the condition that the total memory of the computing node is larger than the memory required by running a corresponding program
Figure DEST_PATH_IMAGE040
Then, the corresponding program running time is calculated by using a monitoring tool integrated with the platform
Figure DEST_PATH_IMAGE041
，
Figure DEST_PATH_IMAGE042
,...,
Figure DEST_PATH_IMAGE043
And application run key features: CPU utilization
Figure DEST_PATH_IMAGE044
，
Figure DEST_PATH_IMAGE045
,...,
Figure DEST_PATH_IMAGE046
And application run key features: memory utilization
Figure DEST_PATH_IMAGE047
,
Figure DEST_PATH_IMAGE048
,...,
Figure DEST_PATH_IMAGE049
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE050
for the program run time(s),
Figure DEST_PATH_IMAGE051
CPU resource utilization (%) occupied for the application,
Figure 790834DEST_PATH_IMAGE052
calculating the scale for the memory resource utilization rate (%) occupied by the application program
Figure DEST_PATH_IMAGE053
Are all according to the factThe actual test scale is scaled to the scaled test scale.
Step S202, determining an operation time state value fitting function, a CPU utilization ratio fitting function and a memory utilization ratio fitting function according to the operation time state value, the CPU utilization ratio and the memory utilization ratio under the corresponding relation of the program, the supercomputer and the computing resources.
Calculating the program running time by the running time state value, the CPU utilization rate and the memory utilization rate under the corresponding relation among the program, the supercomputer and the calculation resources obtained in the step S201
Figure 874108DEST_PATH_IMAGE050
Program CPU utilization
Figure 763567DEST_PATH_IMAGE051
And memory utilization
Figure 298453DEST_PATH_IMAGE052
Estimate the example size
Figure DEST_PATH_IMAGE054
And using computing resources
Figure 818427DEST_PATH_IMAGE055
In relation to (2)
Figure DEST_PATH_IMAGE056
。
At run time
Figure 258505DEST_PATH_IMAGE050
For example, assume a nonlinear curve function of the form
Figure DEST_PATH_IMAGE057
And satisfy
Figure DEST_PATH_IMAGE058
Wherein, in the step (A),
Figure DEST_PATH_IMAGE060
，
Figure 420496DEST_PATH_IMAGE061
then, the result is substituted into an lsqcurvefit function of Matlab, and the least square method is used for estimation, so that a fitting function can be calculated
Figure DEST_PATH_IMAGE062
. By the same token, the method can obtain
Figure DEST_PATH_IMAGE063
. It should be noted that the form of the nonlinear curve function may be modified according to actual situations, and this embodiment is not particularly limited thereto.
Step S203, calculating the running of the target application on the target super computer through the running time state value fitting function, the CPU utilization ratio fitting function and the memory utilization ratio fitting function
Figure 731260DEST_PATH_IMAGE020
And (4) evaluating results of aspects.
In another embodiment provided by the present invention, as shown in fig. 2, the obtaining the memory required by the program includes:
step S301 of acquiring the program
Figure 218874DEST_PATH_IMAGE034
And respectively evaluating the required memories of the operation according to the corresponding histories.
Step S302, determining the memory required by the historical evaluation operation as an initial memory
Figure DEST_PATH_IMAGE064
。
Step S303, passing formula
Figure 270881DEST_PATH_IMAGE040
=
Figure DEST_PATH_IMAGE065
And calculating the memory required by running the corresponding program.
Wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE066
and calculating the node memory on the cluster.
Furthermore, after the memory required for running the corresponding program, the program needs to be monitored and run in real time by calculation
Figure 908667DEST_PATH_IMAGE034
Occupied memory value; if the memory value exceeds a preset value, passing a formula
Figure DEST_PATH_IMAGE067
Re-determining the memory required by running the corresponding program; wherein the content of the first and second substances,
Figure 747308DEST_PATH_IMAGE068
，
Figure DEST_PATH_IMAGE069
。
it should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In an embodiment, a resource performance level determining apparatus of a super computer is provided, where the resource performance level determining apparatus of the super computer corresponds to the resource performance level determining method of the super computer in the above embodiments one to one. As shown in fig. 3, the resource performance level determination apparatus of the super computer has the following functional modules:
an obtaining module 10, configured to obtain a CPU state value, a memory state value, a network state value, and an input/output I/O state value of a central processing unit of a target supercomputer, and an operating time state value, a CPU utilization rate, and a memory utilization rate that are required by a target application to operate under the target supercomputer;
a calculating module 20, configured to add the CPU state value, the memory state value, the network state value, and the I/O state value to obtain a system state value, and add the operating time state value, the CPU utilization, and the memory utilization to obtain an application state value;
and the determining module 30 is configured to determine the resource performance level of the target supercomputer according to the system state value and the application state value.
In an embodiment that may be provided by the present invention, the obtaining module 10 is specifically configured to:
acquiring a first intermediate parameter and a second intermediate parameter which respectively correspond to different evaluation types of the target supercomputer, wherein the evaluation types comprise a CPU (Central processing Unit), a memory, a network and an I/O (input/output);
calculating a state value of the first intermediate parameter by:
Figure DEST_PATH_IMAGE071
；
calculating a state value of the second intermediate parameter by the following formula:
Figure DEST_PATH_IMAGE073
；
obtaining a CPU state value, a memory state value, a network state value and an I/O state value by calculating the sum of the state value of the first intermediate parameter and the state value of the second intermediate parameter belonging to the same evaluation type;
wherein the content of the first and second substances,
Figure 140243DEST_PATH_IMAGE029
for the target supercomputer at
Figure DEST_PATH_IMAGE074
The result of the evaluation of the aspect,
Figure 820492DEST_PATH_IMAGE007
in order for the target super-computer to be,
Figure 714499DEST_PATH_IMAGE008
a first intermediate parameter or a second intermediate parameter respectively corresponding to the evaluation type CPU, the memory, the network and the I/O,
Figure 829217DEST_PATH_IMAGE009
to represent
Figure 783266DEST_PATH_IMAGE008
The significant coefficient of (a) of (b),
Figure 108068DEST_PATH_IMAGE010
，
Figure 55033DEST_PATH_IMAGE011
is a preset fixed value;
Figure 539104DEST_PATH_IMAGE012
to a target supercomputer
Figure 414788DEST_PATH_IMAGE007
In that
Figure 85940DEST_PATH_IMAGE008
Evaluation results of aspects;
Figure 197116DEST_PATH_IMAGE013
for presetting supercomputers
Figure 50540DEST_PATH_IMAGE014
In that
Figure 346392DEST_PATH_IMAGE008
And (4) evaluating results of aspects.
In another embodiment that may be provided by the present invention, the obtaining module 10 is specifically configured to:
acquiring a third intermediate parameter and a fourth intermediate parameter respectively corresponding to different evaluation types of a target application under the target super computer, wherein the evaluation types comprise an operation time state value, a CPU utilization rate and a memory utilization rate;
calculating a state value of the third intermediate parameter by:
Figure DEST_PATH_IMAGE075
；
calculating a state value of the fourth intermediate parameter by:
Figure DEST_PATH_IMAGE076
；
obtaining an operating time state value, a CPU utilization rate and a memory utilization rate by calculating a sum of the state value of the third intermediate parameter and the state value of the fourth intermediate parameter belonging to the same evaluation type;
wherein the content of the first and second substances,
Figure 786732DEST_PATH_IMAGE019
running on the target supercomputer for the target application
Figure 81359DEST_PATH_IMAGE020
The result of the evaluation of the aspect,
Figure DEST_PATH_IMAGE077
for the purpose of the said target application(s),
Figure 353072DEST_PATH_IMAGE007
in order for the target super-computer to be,
Figure 554246DEST_PATH_IMAGE020
a third intermediate parameter or a fourth intermediate parameter respectively corresponding to the evaluation type running time state value, the CPU utilization rate and the memory utilization rate,
Figure 340936DEST_PATH_IMAGE023
to represent
Figure 433395DEST_PATH_IMAGE020
The significant coefficient of (a) of (b),
Figure 746565DEST_PATH_IMAGE024
，
Figure 259585DEST_PATH_IMAGE011
is a preset fixed value;
Figure 143359DEST_PATH_IMAGE025
for the target application
Figure DEST_PATH_IMAGE079
At the target supercomputer
Figure 101825DEST_PATH_IMAGE007
On the upper part
Figure 144868DEST_PATH_IMAGE020
Evaluation results of aspects;
Figure 953424DEST_PATH_IMAGE028
for the target application
Figure 590073DEST_PATH_IMAGE021
On a preset super computer
Figure 509487DEST_PATH_IMAGE014
On the upper part
Figure 672615DEST_PATH_IMAGE020
And (4) evaluating results of aspects.
Further, the obtaining module 10 is also used for obtaining
Figure 901340DEST_PATH_IMAGE033
Programs of different calculation sizes
Figure 274553DEST_PATH_IMAGE034
Are respectively at
Figure 482811DEST_PATH_IMAGE035
Different supercomputers
Figure 500446DEST_PATH_IMAGE036
Provided with
Figure 916384DEST_PATH_IMAGE037
A plurality of different computing resources
Figure 489142DEST_PATH_IMAGE038
Running to obtain a running time state value, a CPU utilization rate and a memory utilization rate under the corresponding relation among the program, the supercomputer and the computing resources; the memory of the node corresponding to the computing resource is larger than the memory required by running the corresponding program;
further, the determining module 30 is further configured to determine an operation time state value fitting function, a CPU utilization ratio fitting function, and a memory utilization ratio fitting function according to the operation time state value, the CPU utilization ratio, and the memory utilization ratio in the corresponding relationship among the program, the supercomputer, and the computing resources;
further, the calculating module 20 is further configured to calculate the target application running on the target supercomputer according to the running time state value fitting function, the CPU utilization ratio fitting function, and the memory utilization ratio fitting function
Figure 15938DEST_PATH_IMAGE020
And (4) evaluating results of aspects.
Further, the obtaining module 10 is further configured to obtain the program
Figure 888079DEST_PATH_IMAGE034
Respectively corresponding memories required by historical evaluation operation;
further, the determining module 30 is further configured to determine the memory required by the historical evaluation operation as an initial memory
Figure 694492DEST_PATH_IMAGE064
；
Further, the calculating module 20 is further configured to calculate the formula
Figure 511139DEST_PATH_IMAGE040
=
Figure 825314DEST_PATH_IMAGE065
Calculating a memory required for running a corresponding program; wherein the content of the first and second substances,
Figure 411016DEST_PATH_IMAGE066
and calculating the node memory on the cluster.
Further, the computing module 20 is further configured to monitor and operate the program in real time
Figure 653910DEST_PATH_IMAGE034
Occupied memory value; if the memory value exceeds a preset value, passing a formula
Figure 957852DEST_PATH_IMAGE067
Re-determining the memory required by running the corresponding program; wherein the content of the first and second substances,
Figure 75719DEST_PATH_IMAGE068
，
Figure DEST_PATH_IMAGE080
。
for the specific limitation of the resource performance level determination apparatus of the super computer, reference may be made to the above limitation of the resource performance level determination method of the super computer, and details are not described here. The various modules in the above-described apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer;
adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
and determining the resource performance level of the target super computer according to the system state value and the application state value.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer;
adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
and determining the resource performance level of the target super computer according to the system state value and the application state value.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (9)

1. A method for resource performance level determination for a supercomputer, the method comprising:
acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target supercomputer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target supercomputer;
adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
determining the resource performance level of the target super computer according to the system state value and the application state value;
will be provided with
Figure 351757DEST_PATH_IMAGE001
Programs of different calculation sizes
Figure 596794DEST_PATH_IMAGE002
Are respectively at
Figure 438848DEST_PATH_IMAGE003
Different supercomputers
Figure 425320DEST_PATH_IMAGE004
Provided with
Figure 302009DEST_PATH_IMAGE005
A plurality of different computing resources
Figure 452368DEST_PATH_IMAGE006
Running to obtain a running time state value, a CPU utilization rate and a memory utilization rate under the corresponding relation among the program, the supercomputer and the computing resources; the memory of the node corresponding to the computing resource is larger than the memory required by running the corresponding program;
determining an operation time state value fitting function, a CPU utilization ratio fitting function and a memory utilization ratio fitting function according to the operation time state value, the CPU utilization ratio and the memory utilization ratio under the corresponding relation among the program, the supercomputer and the computing resources;
calculating the target application running on the target supercomputer by the running time state value fitting function, the CPU utilization ratio fitting function and the memory utilization ratio fitting function
Figure 781718DEST_PATH_IMAGE007
And (4) evaluating results of aspects.
2. The method of claim 1, wherein obtaining the CPU state value, the memory state value, the network state value, and the I/O state value of the target supercomputer comprises:
acquiring a first intermediate parameter and a second intermediate parameter which respectively correspond to different evaluation types of the target supercomputer, wherein the evaluation types comprise a CPU (Central processing Unit), a memory, a network and an I/O (input/output);
calculating a state value of the first intermediate parameter by:
Figure DEST_PATH_IMAGE008
；
calculating a state value of the second intermediate parameter by the following formula:
Figure DEST_PATH_IMAGE010
；
obtaining a CPU state value, a memory state value, a network state value and an I/O state value by calculating the sum of the state value of the first intermediate parameter and the state value of the second intermediate parameter belonging to the same evaluation type;
wherein the content of the first and second substances,
Figure 403454DEST_PATH_IMAGE011
for the target supercomputer at
Figure 134650DEST_PATH_IMAGE012
The result of the evaluation of the aspect,
Figure 691795DEST_PATH_IMAGE013
in order for the target super-computer to be,
Figure 305179DEST_PATH_IMAGE014
a first intermediate parameter or a second intermediate parameter respectively corresponding to the evaluation type CPU, the memory, the network and the I/O,
Figure 104508DEST_PATH_IMAGE015
to represent
Figure 690210DEST_PATH_IMAGE014
The significant coefficient of (a) of (b),
Figure 683836DEST_PATH_IMAGE016
，
Figure 987779DEST_PATH_IMAGE017
is a preset fixed value;
Figure 528481DEST_PATH_IMAGE018
to a target supercomputer
Figure 499849DEST_PATH_IMAGE013
In that
Figure 726693DEST_PATH_IMAGE014
Evaluation results of aspects;
Figure 190035DEST_PATH_IMAGE019
for presetting supercomputers
Figure 331167DEST_PATH_IMAGE020
In that
Figure 891461DEST_PATH_IMAGE014
And (4) evaluating results of aspects.
3. The method of claim 1, wherein obtaining the run-time state value, CPU utilization, and memory utilization required by the target application to run under the target supercomputer comprises
Acquiring a third intermediate parameter and a fourth intermediate parameter respectively corresponding to different evaluation types of a target application under the target super computer, wherein the evaluation types comprise an operation time state value, a CPU utilization rate and a memory utilization rate;
calculating a state value of the third intermediate parameter by:
Figure 226889DEST_PATH_IMAGE021
；
calculating a state value of the fourth intermediate parameter by:
Figure 974266DEST_PATH_IMAGE023
；
obtaining an operating time state value, a CPU utilization rate and a memory utilization rate by calculating a sum of the state value of the third intermediate parameter and the state value of the fourth intermediate parameter belonging to the same evaluation type;
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE024
running on the target supercomputer for the target application
Figure 981405DEST_PATH_IMAGE007
The result of the evaluation of the aspect,
Figure 897670DEST_PATH_IMAGE025
for the purpose of the said target application(s),
Figure 699273DEST_PATH_IMAGE013
in order for the target super-computer to be,
Figure 199525DEST_PATH_IMAGE007
a third intermediate parameter or a fourth intermediate parameter respectively corresponding to the evaluation type running time state value, the CPU utilization rate and the memory utilization rate,
Figure 682459DEST_PATH_IMAGE026
to represent
Figure 718810DEST_PATH_IMAGE007
The significant coefficient of (a) of (b),
Figure 894576DEST_PATH_IMAGE027
，
Figure 882124DEST_PATH_IMAGE017
is a preset fixed value;
Figure 903170DEST_PATH_IMAGE028
for the target application
Figure 516730DEST_PATH_IMAGE029
At the target supercomputer
Figure 128976DEST_PATH_IMAGE013
On the upper part
Figure 603820DEST_PATH_IMAGE007
Evaluation results of aspects;
Figure 428557DEST_PATH_IMAGE030
for the target application
Figure 173921DEST_PATH_IMAGE025
On a preset super computer
Figure 425911DEST_PATH_IMAGE020
On the upper part
Figure 388051DEST_PATH_IMAGE007
And (4) evaluating results of aspects.
4. The method of claim 1, further comprising:
acquiring the program
Figure 16478DEST_PATH_IMAGE002
Respectively corresponding memories required by historical evaluation operation;
determining the memory required by the historical evaluation operation as an initial memory
Figure 350770DEST_PATH_IMAGE031
；
By the formula
Figure 773661DEST_PATH_IMAGE032
=
Figure 19834DEST_PATH_IMAGE033
Calculating a memory required for running a corresponding program;
wherein the content of the first and second substances,
Figure 655215DEST_PATH_IMAGE034
and calculating the node memory on the cluster.
5. The method of claim 4, further comprising:
monitoring and operating the program in real time
Figure 109592DEST_PATH_IMAGE002
Occupied memory value;
if the memory value exceeds a preset value, passing a formula
Figure 765702DEST_PATH_IMAGE035
Re-determining the memory required by running the corresponding program;
wherein the content of the first and second substances,
Figure 436854DEST_PATH_IMAGE036
，
Figure 672664DEST_PATH_IMAGE037
，
Figure DEST_PATH_IMAGE038
the memory required for running the corresponding program in the nth calculation.
6. An apparatus for determining a performance level of a resource of a supercomputer, the apparatus comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring a Central Processing Unit (CPU) state value, a memory state value, a network state value and an input/output (I/O) state value of a target super computer, and an operation time state value, a CPU utilization rate and a memory utilization rate which are required by the running of a target application under the target super computer;
the computing module is used for adding the CPU state value, the memory state value, the network state value and the I/O state value to obtain a system state value, and adding the running time state value, the CPU utilization rate and the memory utilization rate to obtain an application state value;
the determining module is used for determining the resource performance level of the target super computer according to the system state value and the application state value;
an acquisition module for further processing
Figure 43864DEST_PATH_IMAGE001
Programs of different calculation sizes
Figure 74137DEST_PATH_IMAGE002
Are respectively at
Figure 498165DEST_PATH_IMAGE003
Different supercomputers
Figure 773551DEST_PATH_IMAGE004
Provided with
Figure 701056DEST_PATH_IMAGE005
A plurality of different computing resources
Figure 105492DEST_PATH_IMAGE006
Running to obtain a running time state value, a CPU utilization rate and a memory utilization rate under the corresponding relation among the program, the supercomputer and the computing resources; the memory of the node corresponding to the computing resource is larger than the memory required by running the corresponding program;
the determining module is further configured to determine an operating time state value fitting function, a CPU utilization ratio fitting function, and a memory utilization ratio fitting function according to the operating time state value, the CPU utilization ratio, and the memory utilization ratio in the correspondence among the program, the supercomputer, and the computing resources;
the calculation module is further configured to calculate the target application running on the target supercomputer according to the running time state value fitting function, the CPU utilization ratio fitting function, and the memory utilization ratio fitting function
Figure 751237DEST_PATH_IMAGE007
And (4) evaluating results of aspects.
7. The apparatus of claim 6, wherein the obtaining module is specifically configured to:
acquiring a first intermediate parameter and a second intermediate parameter which respectively correspond to different evaluation types of the target supercomputer, wherein the evaluation types comprise a CPU (Central processing Unit), a memory, a network and an I/O (input/output);
calculating a state value of the first intermediate parameter by:
Figure 830314DEST_PATH_IMAGE040
；
calculating a state value of the second intermediate parameter by the following formula:
Figure 612325DEST_PATH_IMAGE042
；
obtaining a CPU state value, a memory state value, a network state value and an I/O state value by calculating the sum of the state value of the first intermediate parameter and the state value of the second intermediate parameter belonging to the same evaluation type;
wherein the content of the first and second substances,
Figure 781139DEST_PATH_IMAGE011
for the target supercomputer at
Figure 914180DEST_PATH_IMAGE012
The result of the evaluation of the aspect,
Figure 531368DEST_PATH_IMAGE013
in order for the target super-computer to be,
Figure 167886DEST_PATH_IMAGE043
a first intermediate parameter or a second intermediate parameter respectively corresponding to the evaluation type CPU, the memory, the network and the I/O,
Figure 710863DEST_PATH_IMAGE015
to represent
Figure 65620DEST_PATH_IMAGE014
The significant coefficient of (a) of (b),
Figure 498219DEST_PATH_IMAGE016
，
Figure 254822DEST_PATH_IMAGE017
is a preset fixed value;
Figure 437542DEST_PATH_IMAGE018
to a target supercomputer
Figure 810754DEST_PATH_IMAGE013
In that
Figure 769745DEST_PATH_IMAGE014
Evaluation results of aspects;
Figure 708751DEST_PATH_IMAGE019
for presetting supercomputers
Figure 859110DEST_PATH_IMAGE020
In that
Figure 955504DEST_PATH_IMAGE014
And (4) evaluating results of aspects.
8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the resource performance level determination method of a supercomputer according to any one of claims 1 to 5 when executing the computer program.
9. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out a method of resource performance level determination of a supercomputer according to any one of claims 1 to 5.
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